Aberdeen & WISE’18 & WSDM’19
阿伯丁访问经历 主要工作： Data-driven ABox consistency checking （人造的场景，人造的数据） 实验室工作中可能值得我们借鉴的： 一个工作可以共同维护一个文档（比如挂在Google Drive上），尤其是多个人合作一个工作的时候 其他： 安静，空气好
WISE’2018 (The 19th International conference on web information systems and engineering) Accepted papers: 47 (long papers) + 22 (short papers)
Research paper sessions Blockchain Information Extraction Social Network Analysis Data Mining Techniques Security Graph Data Data Mining and Applications Web Applications Internet of Things Data Analysis and Applications Social Network and Security Recommender Systems Text Mining Data Stream and Distributed Computing Recommender Systems 2 Cloud Computing Entity Linkage and Semantics
WISE总结 论文杂（主题，内容） 好中 全是中国人
WSDM’2019 (12th ACM International Conference on Web Search and Data Mining) Accepted papers: 84/511 (16.4%)
Research paper sessions Search and Ranking Knowledge Graphs and Analytics Recommendation and Temporal Trends Privacy Understanding Conversation, Discussion, Opinions Networks and Social Behavior E-commerce and Recommendation Causal Learning Recommendation Personalization and Characterizing User Behavior Domain Transfer and Representation Learning Text Understanding
Knowledge Graph and Analytics Representation Interpretation with Spatial Encoding and Multimodal Analytics. Ninghao Liu, Mengnan Du, Xia Hu (Texas A&M University, USA). Interaction Embeddings for Prediction and Explanation in Knowledge Graphs. Wen Zhang (Zhejiang University, China); Bibek Paudel (University of Zurich, Switzerland); Wei Zhang (Alibaba Group, China); Abraham Bernstein (ETH Zurich, Switzerland); Huajun Chen (Zhejiang University, China). * Knowledge Graph Embedding Based Question Answering. Xiao Huang, Jingyuan Zhang, Dingcheng Li, Ping Li (Baidu, USA). *考虑了预测时头实体和关系间的交互（关系决定了预测过程中哪些头实体信息有用，这些头实体信息 又决定了用什么样的信息去推理出尾实体）
WSDM特点 偏实用，受工业界关注（尤其是推荐相关） 近两年WSDM主流的工作还是以机器学习相关的方法为主 传统DM圈的会（Jiawei Han, Philip Yu, Huan Liu…），跟我们组风 格不是很一致 不好中（按国内的标准性价比低）